基于卡尔曼滤波的短波等幅报降噪技术研究
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摘要
本文研究的是短波莫尔斯电报信号的噪声抑制处理技术。在无线通信系统中,噪声信号的干扰是影响通信效果的主要原因。由于短波莫尔斯电报通信属于模拟通信的制式,依赖电离层天波反射和地波传输,对信道依赖性较强,随着工业电气化的发展,短波信道受到的干扰日益严重,莫尔斯信号传输质量急剧恶化,导致电台值班抄收水平日益下降,给从事人工守听抄收莫尔斯电报信号的报务员带来较大负担。本文研究的目的是使用数字信号处理技术,在不改动原有电台设备硬件结构的基础上,搭建在线的信号处理模块作为电台的后级音频处理系统,对电台输出的莫尔斯音频信号进行降噪处理后,提升莫尔斯音频信号的信噪比,改善莫尔斯音频信号的听感,在降低无线电报务值班人员劳动强度的基础上,提高值班电报信号抄收的准确率,提升电台值班业务水平。
     在前人研究工作的基础上,本文首先对莫尔斯电码自身的点划及字符间的相关规律进行了分析,研究了影响莫尔斯电报信号的噪声类型,讨论了噪声对莫尔斯信号的污染方式,分析了短波通信设备架设方式对莫尔斯电报信号噪声的影响,研究了电报抄收人员在噪声干扰状态下实现人工抗噪声抄收的原理。根据莫尔斯信号电码的自相关特性,分析了人脑在记忆和识别莫尔斯电报信号中的分析处理过程,研究了在发报手法不均状态下,抄收人员抗噪声处理的方法。分析了莫尔斯信号现有的降噪处理技术,建立了短波莫尔斯电报信号的空间状态模型,应用卡尔曼滤波算法对其进行了推导,建立了卡尔曼滤波模型。探讨了卡尔曼滤波在短波莫尔斯电报信号音频滤波方法,在CCS环境下编写了卡尔曼滤波算法的DSP程序,结合现有值班电台的音频输出接口,搭建了以DSP5402和AIC23为核心的数字信号降噪处理模块,使用AIC23对电台输出的音频信号进行模数采样,在DSP5402中使用卡尔曼滤波程序对莫尔斯音频信号进行降噪处理,处理后音频信号通过AIC23耳机接口输出给报务员抄收。
     为了验证卡尔曼滤波处理对莫尔斯音频信号的降噪处理性能,本文模拟了一段受高斯白噪声污染的莫尔斯音频信号,使用计算输出信噪比的方法,将卡尔曼滤波器与传统的窄带滤波器进行了对比试验,实验结果表明,卡尔曼滤波算法对系统参数和噪声的统计特性估计模型决定了卡尔曼滤波对莫尔斯信号的降噪处理性能,在莫尔斯信号的信噪比较大时,卡尔曼滤波器完全能够达到窄带滤波器的降噪效果。
In this paper, the short-wave morse telegraph signal noise reduction technology is discussed. In the wireless communication system, noise interference is the main effect of communication. Because short-wave morse telegraph communication belongs to the analog communication standard, it depends on the sky wave ionospheric reflection and ground wave transmission, as well as the channel. With the development of industrial electrification, the interference the short-wave channel suffers is growing, the quality of the transmission of morse signal has a sharp deterioration. It leds to declining levels of radio duty collecting, it makes it very difficult for the operator to listen to the morse telegraph telegraph signals. The purpose of this paper is to use the digital signal processing technology to build a online signal processing module to be after-level of the radio audio processing system, on the basis of no alteration of the original radio equipment hardware. After denoising of morse audio signal out from radio, it can raise the SNR of the morse audio signal, improve the listening sense of the morse audio signal, on the basis of reducing the labor intensity of radio wireless telegraphy service operator, improve the accuracy of collecting duty, and enhance the business level of professional skill.
     Based on the previous studies, this paper first analyze the dot-and-dash of morse and the rules and the correlation between characters, it also study the effects of type of noise of morse signal, discuss the pollution mode of the morse signal, analyze the influence of the noise of short-wave communication which the erection methods of equipment makes, it studys the principle of artificial collecting of noise can achieve by collecting telegraph officers in noise state. According to signal autocorrelation of morse code, it analyzes the signal processing of human brain in memory and recognition of morse telegraphy. It studys ways to deal with anti-noise of collecting staff with a uneven way in transmitter mode. It analyzes the existing noise reduction technology in morse signal, establish a short space state model of morse telegraph. It uses kalman filter algorithm to conduct the derivation, and kalman filter model was established.it investigates the audio filter method of kallman filtering in short-wave morse telegraphy signal and writes the DSP code in CCS environment, with the combine of existing audio output interface in duty stations, it builds a digital signal denoiseprocessing module with the core of DSP5402 and AIC23, uses the AIC23 to do the AD sampling of audio signals out from the radio, and use the kalman filter algorithm to conduct the denoising of morse audio signal in DSP5402, after processing, the audio signal output to the radio operator for collecting through the AIC23 headphone.
     In order to verify the performance of the noise reduction of kalman filter to the morse audio signal, we simulated an audio signal morse white a gaussian noise, use the method of calculation of the output SNR to take a contrast experiment of kalman filter and the traditional narrow-band filter. The results show that it is estimation model which kalman filter algorithm make for system parameters and noise statistics decides the performance of kalman filter can achieve in noise reduction of morse signal. When SNR of morse signal is larger, kalman filter is fully able to meet the noise reduction effect of narrow-band filter
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